本文關(guān)鍵詞：顱腦損傷昏迷患者蘇醒的影響因素分析　出處：《新鄉(xiāng)醫(yī)學(xué)院》2015年碩士論文　論文類型：學(xué)位論文

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【摘要】：目的顱腦損傷(brain injury)是神經(jīng)外科急危重癥之一,預(yù)后差,致殘率、致死率高,對人類健康和生命造成嚴重危害。我國顱腦損傷的發(fā)病率為100-200/10萬人,18%-20%為重型顱腦損傷,30%-50%最終死亡,每年因此造成的經(jīng)濟損失達數(shù)百億。重型顱腦損傷患者通常合并昏迷,對顱腦損傷昏迷患者能否蘇醒的預(yù)測和評估,對重型顱腦損傷患者臨床治療方案的制定有著重要的意義。目前,顱腦損傷昏迷預(yù)后的研究涵蓋了以下幾個方面：神經(jīng)系統(tǒng)檢查如瞳孔改變和GCS評分,影像學(xué)檢查如頭顱CT、MRI,神經(jīng)電生理學(xué)檢查如腦電圖(EEG)和誘發(fā)電位,以及生理生化如血糖、血鈉、腦脊液SB100等改變。但是由于各地區(qū)醫(yī)療設(shè)備以及醫(yī)療水平差異很大,因此在醫(yī)療設(shè)備欠發(fā)達地區(qū),特別是在基層醫(yī)院評估手段受到很大的限制。本研究的目的是為了探討顱腦損傷昏迷患者預(yù)后影響因素,建立顱腦損傷后預(yù)測昏迷患者蘇醒率的模型,協(xié)助臨床醫(yī)師進行臨床決策的制定。方法回顧性分析2009年2月-2014年2月河南省安陽地區(qū)醫(yī)院神經(jīng)外科共收治380例顱腦損傷昏迷患者,了解患者預(yù)后情況即是否蘇醒。收集患者19項可能影響因素包括：性別、年齡、瞳孔大小、瞳孔對光反應(yīng)變化、入院時GCS評分情況、呼吸異常、復(fù)合傷、血壓、心率、中線移位情況、顱內(nèi)血腫量、環(huán)池及腦干形態(tài)變化、腦干聽覺誘發(fā)電位(BAEP)變化、是否有消化道出血、血糖值、是否合并高鈉血癥、是否合并顱內(nèi)感染、是否合并肺部感染、是否合并腦積水。采用SPSS 19.0統(tǒng)計軟件分析,對各項可能影響因素進行單因素分析,多因素分析采用Logistic回歸分析,確定影響患者蘇醒率的因素,并且建立回歸方程。其中檢驗水準α=0.05。結(jié)果1本研究共入組380例患者,在隨訪期限內(nèi),蘇醒192例(50.5%),未蘇醒188例(49.5%)。年齡、性別、心率異常、顱內(nèi)血腫量等4項與患者蘇醒率無關(guān)(P0.05)；呼吸異常、低血壓、是否合并其他部位損傷、瞳孔對光反射消失、是否出現(xiàn)瞳孔散大、中線移位的程度、GCS評分高低、中腦周圍池變化的程度、腦干聽覺誘發(fā)電位異常、高鈉血癥、消化道出血、肺部感染、顱內(nèi)感染、腦積水、血糖值等15項與患者蘇醒率存在相關(guān)性(P0.05)。對單因素分析中的15個有影響的因素進行Logistic回歸分析,呼吸異常、環(huán)池及腦干形態(tài)變化分級、腦干聽覺誘發(fā)電位異常、GCS分組、腦積水、顱內(nèi)感染等6項與顱腦損傷昏迷患者蘇醒率之間存在顯著相關(guān)性(P0.05)。2建立回歸方程：Logistic(P)=19.135+2.872Xi+2.341X2-25.516X3.1-23.021X3.2-20.844X3.3-19.554X3.4+ 0.996X3.5+3.612X4+2.487X5+2.521X6.本研究所建立的回歸模型總體判對率為92.6%，，模型的Nagelkerke決定系數(shù)R2=0.850。結(jié)論1.GCS評分、呼吸異常、環(huán)池和腦干形態(tài)變化、腦干聽覺誘發(fā)電位異常、伴發(fā)顱內(nèi)感染、腦積水6項因素是影響顱腦損傷患者預(yù)后的顯著性因素。2.本研究所建立的回歸模型可為臨床工作中對顱腦損傷昏迷患者能否蘇醒的預(yù)測提供有效且簡便的方法,為此類患者臨床治療方案的制定提供可靠的依據(jù),有利于合理分配醫(yī)療衛(wèi)生資源。
[Abstract]:Objective craniocerebral injury (brain injury) is one of the critical and critical diseases in the Department of neurosurgery. The prognosis is poor, the rate of disability and death is high, and it is serious harm to human health and life. The incidence of craniocerebral injury in China is 100-200/10 million, 18%-20% is a severe head injury, and 30%-50% eventually dies, and the economic loss is hundreds of billions of dollars a year. Severe craniocerebral injury is usually associated with coma. It is of great significance to predict and assess coma recovery in patients with traumatic brain injury, and to formulate a clinical treatment plan for patients with severe head injury. At present, the prognosis of head injury coma research covers the following aspects: the examination of the nervous system such as pupil change and GCS score, imaging examination such as brain CT, MRI, electrophysiological examinations such as EEG and evoked potentials (EEG), and the physiological and biochemical blood glucose, blood sodium, cerebrospinal fluid SB100 change. However, due to the large difference of medical devices and medical level in different regions, the evaluation methods in the less developed areas of medical equipment, especially in the grass-roots hospitals, are greatly limited. The purpose of this study is to explore the prognostic factors of coma patients after craniocerebral injury, and establish a model to predict the recovery rate of coma patients after craniocerebral injury, so as to assist clinicians in making clinical decisions. Methods a retrospective analysis of 380 cases of craniocerebral injury comatose patients in Department of Neurosurgery, Anyang District Hospital of Henan province from February 2009 to February -2014, was carried out to know the prognosis of patients. Collect 19 patients may influence factors include: gender, age, pupil size, pupillary light responses, admission GCS score, abnormal breathing, blood pressure, heart rate, combined injuries, midline shift, intracranial hematoma volume, ring pool and morphological changes of brainstem, brainstem auditory evoked potential (BAEP) changes, whether with gastrointestinal bleeding, blood glucose, whether with hypernatremia, whether complicated with intracranial infection, pulmonary infection, whether patients with hydrocephalus. SPSS 19 statistical software was used to analyze the possible factors. Univariate analysis was performed. Multivariate regression analysis was used to identify the factors influencing the recovery rate of patients, and establish regression equation. Results the Logistic regression analysis was used to establish the regression equation. The test level was alpha =0.05. Results in the 1 study, 380 patients were enrolled in the study. During the period of follow-up, 192 cases (50.5%) were awakened and 188 (49.5%) were not recovered. Age, gender, abnormal heart rate, volume of intracranial hematoma and 4 patients with recovery rate independent (P0.05); abnormal breathing, low blood pressure, whether associated injuries, pupillary light reflex, or mydriasis, midline shift, GCS score, perimesencephalic change degree, brainstem auditory evoked potential anomalies, hypernatremia, digestive tract hemorrhage, pulmonary infection, intracranial infection, hydrocephalus, blood glucose of 15 patients with recovery rate correlation (P0.05). On the 15 influential factors in univariate analysis were analyzed by Logistic regression analysis, abnormal breathing, ring pool and brainstem classification, morphological changes of brainstem auditory evoked potential abnormalities, GCS group, hydrocephalus, intracranial infection and 6 with craniocerebral injury and coma significant correlation between patients' recovery rate (P0.05). 2, a regression equation is established: Logistic (P) =19.135+2.872Xi+2.341X2-25.516X3.1-23.021X3.2-20.844X3.3-19.554X3.4+ 0.996X3.5+3.612X4+2.487X5+2.521X6.. The overall judgement rate of the regression model established by this research is 92.6%, and the Nagelkerke coefficient of R2=0.850 of the model is R2=0.850. Conclusion 1.GCS score, respiratory abnormalities, morphological changes of the cisterna and brainstem, brainstem auditory evoked potential abnormalities, intracranial infection and hydrocephalus are 6 factors that influence the prognosis of patients with craniocerebral injury. 2., the regression model established by this study can provide an effective and simple method for predicting the recovery of coma patients with traumatic brain injury in clinical work, providing a reliable basis for the formulation of clinical treatment plan for such patients, and is conducive to the rational allocation of medical and health resources.
【學(xué)位授予單位】：新鄉(xiāng)醫(yī)學(xué)院
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：R651.15

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